San Giovanni al Natisone, Italy
San Giovanni al Natisone, Italy

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Boccardi M.,LENITEM Laboratory of Epidemiology | Ganzola R.,LENITEM Laboratory of Epidemiology | Rossi R.,Psychosocial Rehabilitation Unit | Sabattoli F.,LENITEM Laboratory of Epidemiology | And 8 more authors.
Human Brain Mapping | Year: 2010

Posterior hippocampal volumes correlate negatively with the severity of psychopathy, but local morphological features are unknown. The aim of this study was to investigate hippocampal morphology in habitually violent offenders having psychopathy. Manual tracings of hippocampi from magnetic resonance images of 26 offenders (age: 32.5 ± 8.4), with different degrees of psychopathy (12 high, 14 medium psychopathy based on the Psychopathy Checklist Revised), and 25 healthy controls (age: 34.6 ± 10.8) were used for statistical modelling of local changes with a surface-based radial distance mapping method. Both offenders and controls had similar hippocampal volume and asymmetry ratios. Local analysis showed that the high psychopathy group had a significant depression along the longitudinal hippocampal axis, on both the dorsal and ventral aspects, when compared with the healthy controls and the medium psychopathy group. The opposite comparison revealed abnormal enlargement of the lateral borders in both the right and left hippocampi of both high and medium psychopathy groups versus controls, throughout CA1, CA2-3 and the subicular regions. These enlargement and reduction effects survived statistical correction for multiple comparisons in the main contrast (26 offenders vs. 25 controls) and in most subgroup comparisons. A statistical check excluded a possible confounding effect from amphetamine and polysubstance abuse. These results indicate that habitually violent offenders exhibit a specific abnormal hippocampal morphology, in the absence of total gray matter volume changes, that may relate to different autonomic modulation and abnormal fear-conditioning. © 2009 Wiley-Liss, Inc.

PubMed | University of Trento, University of Genoa, University of Barcelona, LENITEM Laboratory of Epidemiology and 15 more.
Type: Journal Article | Journal: Human brain mapping | Year: 2016

Free water elimination (FWE) in brain diffusion MRI has been shown to improve tissue specificity in human white matter characterization both in health and in disease. Relative to the classical diffusion tensor imaging (DTI) model, FWE is also expected to increase sensitivity to microstructural changes in longitudinal studies. However, it is not clear if these two models differ in their test-retest reproducibility. This study compares a bi-tensor model for FWE with DTI by extending a previous longitudinal-reproducibility 3T multisite study (10 sites, 7 different scanner models) of 50 healthy elderly participants (55-80 years old) scanned in two sessions at least 1 week apart. We computed the reproducibility of commonly used DTI metrics (FA: fractional anisotropy, MD: mean diffusivity, RD: radial diffusivity, and AXD: axial diffusivity), derived either using a DTI model or a FWE model. The DTI metrics were evaluated over 48 white-matter regions of the JHU-ICBM-DTI-81 white-matter labels atlas, and reproducibility errors were assessed. We found that relative to the DTI model, FWE significantly reduced reproducibility errors in most areas tested. In particular, for the FA and MD metrics, there was an average reduction of approximately 1% in the reproducibility error. The reproducibility scores did not significantly differ across sites. This study shows that FWE improves sensitivity and is thus promising for clinical applications, with the potential to identify more subtle changes. The increased reproducibility allows for smaller sample size or shorter trials in studies evaluating biomarkers of disease progression or treatment effects. Hum Brain Mapp 38:12-26, 2017. 2016 Wiley Periodicals, Inc.

PubMed | University of Trento, University of Genoa, University of Barcelona, University of Leipzig and 16 more.
Type: Journal Article | Journal: Human brain mapping | Year: 2016

Understanding how to reduce the influence of physiological noise in resting state fMRI data is important for the interpretation of functional brain connectivity. Limited data is currently available to assess the performance of physiological noise correction techniques, in particular when evaluating longitudinal changes in the default mode network (DMN) of healthy elderly participants. In this 3T harmonized multisite fMRI study, we investigated how different retrospective physiological noise correction (rPNC) methods influence the within-site test-retest reliability and the across-site reproducibility consistency of DMN-derived measurements across 13 MRI sites. Elderly participants were scanned twice at least a week apart (five participants per site). The rPNC methods were: none (NPC), Tissue-based regression, PESTICA and FSL-FIX. The DMN at the single subject level was robustly identified using ICA methods in all rPNC conditions. The methods significantly affected the mean z-scores and, albeit less markedly, the cluster-size in the DMN; in particular, FSL-FIX tended to increase the DMN z-scores compared to others. Within-site test-retest reliability was consistent across sites, with no differences across rPNC methods. The absolute percent errors were in the range of 5-11% for DMN z-scores and cluster-size reliability. DMN pattern overlap was in the range 60-65%. In particular, no rPNC method showed a significant reliability improvement relative to NPC. However, FSL-FIX and Tissue-based physiological correction methods showed both similar and significant improvements of reproducibility consistency across the consortium (ICC=0.67) for the DMN z-scores relative to NPC. Overall these findings support the use of rPNC methods like tissue-based or FSL-FIX to characterize multisite longitudinal changes of intrinsic functional connectivity. Hum Brain Mapp 37:2114-2132, 2016. 2016 Wiley Periodicals, Inc.

Boccardi M.,LENITEM Laboratory of Epidemiology | Frisoni G.B.,LENITEM Laboratory of Epidemiology | Hare R.D.,University of British Columbia | Cavedo E.,LENITEM Laboratory of Epidemiology | And 11 more authors.
Psychiatry Research - Neuroimaging | Year: 2011

Psychopathy is characterized by abnormal emotional processes, but only recent neuroimaging studies have investigated its cerebral correlates. The study aim was to map local differences of cortical and amygdalar morphology. Cortical pattern matching and radial distance mapping techniques were used to analyze the magnetic resonance images of 26 violent male offenders (age: 32 ± 8) with psychopathy diagnosed using the Psychopathy Checklist-Revised (PCL-R) and no schizophrenia spectrum disorders, and in matched controls (age: 35 ± 11). The cortex displayed up to 20% reduction in the orbitofrontal and midline structures (corrected p< 0.001 bilaterally). Up to 30% tissue reduction in the basolateral nucleus, and 10-30% enlargement effects in the central and lateral nuclei indicated abnormal structure of the amygdala (corrected p= 0.05 on the right; and symmetrical pattern on the left). Psychopathy features specific morphology of the main cerebral structures involved in cognitive and emotional processing, consistent with clinical and functional data, and with a hypothesis of an alternative evolutionary brain development. © 2011 Elsevier Ireland Ltd.

Lorenzi M.,LENITEM Laboratory of Epidemiology | Donohue M.,University of California at San Diego | Paternico D.,LENITEM Laboratory of Epidemiology | Scarpazza C.,LENITEM Laboratory of Epidemiology | And 4 more authors.
Neurobiology of Aging | Year: 2010

Clinical trials of disease modifying drugs for Alzheimer's disease (AD) in patients with mild cognitive impairment (MCI) might benefit from enrichment with true AD cases. Four hundred five MCI patients (143 converters and 262 nonconverters to AD within 2 years) of the Alzheimer's disease Neuroimaging Initative (ADNI) were used. Markers for enrichment were hippocampal atrophy on magnetic resonance (MRI), temporoparietal hypometabolism on FDG PET, cerebrospinal fluid (CSF) biomarkers (Abeta42, tau, and phospho-tau), and cortical amyloid deposition (11C-PIB positron emission tomography (PET)). Two separate enrichment strategies were tested to A) maximize the proportion of MCI converters screened in, and B) minimize the proportion of MCI converters screened out. Based on strategy A, when compared with no enrichment and ADAS-Cog as an outcome measure (sample size of 834), enrichment with 18F-FDG PET and hippocampal volume lowered samples size to 260 and 277 cases per arm, but at the cost of screening out 1,597 and 434 cases per arm. When compared with no enrichment and clinical dementia rating (CDR-SOB) as an outcome measure (sample size of 674), enrichment with hippocampal volume and Abeta42 lowered sample sizes to 191 and 291 cases per arm, with 639 and 157 screened out cases. Strategy B reduced the number of screened out cases (740 for [11C]-PIB PET, 101 hippocampal volume, 82 ADAS-COG and 330 for [18F]-FDG PET) but at the expense of decreased power and a relative increase size (740 for [11C]-PIB PET, 676 for hippocampal volume, 744 for ADAS-Cog, and 517 for [18F]-FDG PET). Enrichment comes at the price of an often relevant proportion of screened out cases, and in clinical trial settings, the balance between enrichment of screened in and loss of screened out patients should be critically discussed. © 2010 Elsevier Inc.

PubMed | Overdale Hospital, LENITEM Laboratory of Epidemiology, National Institute of Nuclear Physics, Italy, CNR Institute of Intelligent Systems for Automation and University of Bari
Type: | Journal: Pattern analysis and applications : PAA | Year: 2016

The automated identification of brain structure in Magnetic Resonance Imaging is very important both in neuroscience research and as a possible clinical diagnostic tool. In this study, a novel strategy for fully automated hippocampal segmentation in MRI is presented. It is based on a supervised algorithm, called RUSBoost, which combines data random undersampling with a boosting algorithm. RUSBoost is an algorithm specifically designed for imbalanced classification, suitable for large data sets because it uses random undersampling of the majority class. The RUSBoost performances were compared with those of ADABoost, Random Forest and the publicly available brain segmentation package, FreeSurfer. This study was conducted on a data set of 50 T1-weighted structural brain images. The RUSBoost-based segmentation tool achieved the best results with a Dices index of [Formula: see text] ([Formula: see text]) for the left (right) brain hemisphere. An independent data set of 50 T1-weighted structural brain scans was used for an independent validation of the fully trained strategies. Again the RUSBoost segmentations compared favorably with manual segmentations with the highest performances among the four tools. Moreover, the Pearson correlation coefficient between hippocampal volumes computed by manual and RUSBoost segmentations was 0.83 (0.82) for left (right) side, statistically significant, and higher than those computed by Adaboost, Random Forest and FreeSurfer. The proposed method may be suitable for accurate, robust and statistically significant segmentations of hippocampi.

Caroli A.,LENITEM Laboratory of Epidemiology | Caroli A.,Mario Negri Institute for Pharmacological Research | Frisoni G.B.,LENITEM Laboratory of Epidemiology
Neurobiology of Aging | Year: 2010

The aim of this study was to investigate the dynamics of four of the most validated biomarkers for Alzheimer's disease (AD), cerebro-spinal fluid (CSF) Aβ 1-42, tau, hippocampal volume, and FDG-PET, in patients at different stage of AD. Two hundred twenty-nine cognitively healthy subjects, 154 mild cognitive impairment (MCI) patients converted to AD, and 193 (95 early and 98 late) AD patients were selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. For each biomarker, individual values were Z-transformed and plotted against ADAS-cog scores, and sigmoid and linear fits were compared. For most biomarkers the sigmoid model fitted data significantly better than the linear model. Aβ 1-42 time course followed a steep curve, stabilizing early in the disease course. CSF tau and hippocampal volume changed later showing similar monotonous trends, reflecting disease progression. Hippocampal loss trend was steeper and occurred earlier in time in APOE ε4 carriers than in non-carriers. FDG-PET started changing early in time and likely followed a linear decline. In conclusion, this study provides the first evidence in favor of the dynamic biomarker model which has recently been proposed. © 2010 Elsevier Inc.

Agostini A.,University of Bologna | Benuzzi F.,University of Modena and Reggio Emilia | Filippini N.,University of Oxford | Filippini N.,LENITEM Laboratory of Epidemiology | And 10 more authors.
Neurogastroenterology and Motility | Year: 2013

Background Crohn's disease (CD) is a chronic intestinal disorder characterized by overproduction of inflammatory cytokines and recurrent abdominal pain. Recently, brain morphological abnormalities in the pain matrix were found in patients with chronic pain disorders including irritable bowel syndrome. To investigate potential structural brain changes associated with CD, we used magnetic resonance imaging (MRI). Furthermore, we tested whether in patients gray matter (GM) volumes correlated with disease duration. Methods Eighteen CD patients in remission and 18 healthy controls underwent structural MRI. Voxel-based morphometry (VBM) is a fully automated technique allowing identification of regional differences in the amount of GM enabling an objective analysis of the whole brain between groups of subjects. VBM was used for comparisons and correlation analysis. Key Results With respect to controls, CD patients exhibited decreased GM volumes in portion of the frontal cortex and in the anterior midcingulate cortex. Disease duration was negatively correlated with GM volumes of several brain regions including neocortical and limbic areas. Conclusions & Inferences Crohn's disease is associated with brain morphological changes in cortical and subcortical structures involved in nociception, emotional, and cognitive processes. Our findings provide new insight into the brain involvement in chronic inflammatory bowel disorders. © 2012 Blackwell Publishing Ltd.

Bellelli G.,University of Milan Bicocca | Bernardini B.,Humanitas, Inc. | Pievani M.,LENITEM Laboratory of Epidemiology | Frisoni G.B.,LENITEM Laboratory of Epidemiology | And 2 more authors.
Rejuvenation Research | Year: 2012

Adverse clinical events (ACEs) are common in post-acute hospital care. We aimed at developing and validating a method, able to be administered in hospital wards, for identifying elderly patients at increased risk of ACEs after transferral to post-acute care (PAC) facilities. This was a prospective observational study, including 502 patients admitted to 19 PAC facilities in northern Italy from July 1st to August 14th, 2009. A standardized form was used to collect data. Variables showing stable association with ACEs in testing group were used to derive the score. The relative risk (RR) of developing ACEs according to the score was measured in the validation group. Age ≥87 years, delirium, pressure sore, indwelling bladder catheter, malnutrition, and acute infection on admission were identified as stable ACE predictors. A score of 1 was assigned to each predictor. Subjects were classified as having low (score=0), medium-low (score=1), medium-high (score=2-3), or high (score≥4) risk of ACEs. The RR of developing ≥1 ACE increased progressively from low (RR=1) to medium-low (RR=1.5, 95% confidence interval [CI] 1.1-1.9), medium-high (RR=1.6, 95% CI 1.3-2.1), and high (RR=1.8, 95% CI 1.4-2.3) risk score. The RR of being not discharged to home increased monotonically from 1.0 in low-risk to 2.7 in high-risk groups. In conclusion, this study proposes a method, able to be administered in hospital wards, for identifying patients at increased risk of ACEs after transferral to PAC. The score might also be used to identify people who will not return to home after PAC discharge. © Copyright 2012, Mary Ann Liebert, Inc.

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